Cerebras
Free tierFast AI inference on wafer-scale chips
Free tier available·All audiences·Powered by Cerebras (own hardware/inference); supports models including Qwen, GPT-5.6 Sol, Kimi K2.6, Codex-Spark, Meta Scout, and others·API available
Key strengths
Ultra-fast inference (up to 30x faster than GPUs)Wafer-Scale Engine hardwareOpenAI API compatibilityOn-premise and cloud deploymentEnterprise-grade scalabilityLow latency for real-time AI applications
Free tier + paid plans
Sunnyvale, USA
Founded 2015
Self-hostable
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Use Cases — Technical
Cerebras's Wafer-Scale Engine infrastructure and OpenAI-compatible API make it particularly well-suited for the following technical scenarios:
- Real-time AI inference — Ultra-low latency (up to 30x faster than GPUs) enables synchronous, streaming, and interactive AI features where response time is critical (e.g., coding assistants, live chat, agent loops)
- High-throughput batch workloads — Enterprise-grade scalability supports large-scale inference pipelines without GPU bottlenecks
- Drop-in GPU replacement — OpenAI API compatibility means teams can redirect existing inference traffic to Cerebras endpoints with minimal code changes
- On-premise / air-gapped deployments — Self-hosting support makes Cerebras viable for regulated industries (finance, healthcare, government) requiring data residency
- Multi-model serving — Access to models including Qwen, GPT-5.6 Sol, Kimi K2.6, Codex-Spark, and Meta Scout from a single inference provider
- Edge and serverless AI — Vercel integration enables low-latency AI at the edge for web applications
- Cloud marketplace procurement — AWS Marketplace availability simplifies procurement and consolidated billing for enterprise engineering teams
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